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Allainclair – Python, Flask, FastAPI, experts in Lemon.io

Allainclair

From Brazil

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Back-end Web DeveloperMiddle-to-senior
Hire developer
9 years of commercial experience
Advertising
Art and creativity
Cybersecurity
Entertainment
Information services
Logistics
Scientific research
Smart cities
Social media
Embedded software
NLP software
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Allainclair – Python, Flask, FastAPI

Ever since he was a teenager, Allainclair has been passionate about computers. Every day, he strives to improve his skills and knowledge as a tech professional. He has extensive experience in Data Science and previously worked as a Computer Science professor's assistant, educating students about algorithms, data structures, and object-oriented programming. Currently, he is concentrating on back-end development and is eager to take on new challenges.

Main technologies
Python
7 years
Flask
3 years
FastAPI
3 years
Additional skills
React
SQL
Linux
Java
SQLite
MySQL
Linux
Data Science
SQLAlchemy
Pandas
JavaScript
Kibana
C
R
Bash
Machine learning
scikit-learn
Apache Kafka
Apache Spark
ElasticSearch
C++
Django
Docker
AWS
PostgreSQL
Redis
RabbitMQ
Rewards and achievements
Big tech veteran
Ready to start
ASAP
Direct hire
Potentially possible

Experience Highlights

Backend engineer
Sep 2022 - May 20238 months
Project Overview

Designing, creating, and maintaining a backend service integrating load boards across North America.

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Responsibilities:
  • Designed from scratch and developed REST API service using FastAPI, PostgreSQL, RabbitMQ, Redis, AWS;
  • Integrate REST API with different providers (load boards);
  • Wrote unit and end-to-end tests;
Project Tech stack:
FastAPI
PostgreSQL
RabbitMQ
Redis
AWS
SQLAlchemy
Docker
Full Stack Software Engineer
Aug 2019 - Jun 20222 years 9 months
Project Overview

It is a large social network where any user can be inspired by the pins of the platform.

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Responsibilities:

Allainclair has worked for almost three years as a backend and full-stack engineer maintaining internal tools for the Ads & Growth and Trust and Safety teams.

Main accomplishments:

  • created front-end and back-end features for the Pinterest internal tools;
  • maintained the reliability and stability of the systems by improving their observability;
  • wrote unit and integration tests for frontend (React) and backend (Python);
  • designed new features according to product and engineering requirements;
  • integrated new features with some internal systems.
Project Tech stack:
Python
MySQL
Flask
React
Assistant Professor
Mar 2019 - Oct 20197 months
Project Overview

Computer Science chair.

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Responsibilities:

Allainclair ministered the following subjects:

  • Algorithms and Data Structures;
  • Relational Database;
  • Multi and Hypermedia Systems;
  • Algorithm Analysis and Graph Theory;
  • Object-Oriented Programming.
Project Tech stack:
Java
Python
SQL
SQLite
Data Scientist, Software Engineer
Oct 2015 - Oct 20194 years
Project Overview

Smart traffic lights (STL) hardware and software, that can sense streets using cameras and act (open/close) autonomously.

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Responsibilities:

Main accomplishments:

  • conducted research in traffic optimization area by using smart traffic lights;
  • created a traffic simulator using SUMO (Simulation of Urban MObility). The main algorithm on this simulator had 200% to 400% waiting time optimization on light to medium vehicle traffic;
  • designed and developed optimization algorithms for smart traffic lights;
  • worked closely with hardware and software teams to develop many features of the STL;
  • designed and create embedded distributed real-time systems for the STL with a microservice architecture.
Project Tech stack:
Python
MySQL
Linux
Data Scientist
May 2018 - Feb 20199 months
Project Overview

It is a startup that advises clients on security issues. It offered a system to analyze social network messages, like Twitter, using Natural Language Process techniques to alert the clients.

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Responsibilities:

Main accomplishments:

  • created spam and classifier models using Naive Bayes based on Twitter messages;
  • developed clustering models to aggregate similar messages;
  • used Python/Scikit-learn and Java to create the machine learning models;
  • deployed the models integrating with Elasticsearch and Apache Kafka.
Project Tech stack:
Java
Python
Linux
ElasticSearch

Education

2016
Computer Science
Master's degree

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